AI Engineer

Job Summary

We are seeking a highly skilled Generative AI Engineer to design, develop, and deploy advanced AI-powered solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern cloud-native architectures.

Design, Build, and Deploy

• Design and deploy LLM-powered applications and intelligent automation solutions for enterprise and mission-focused environments.
• Integrate Large Language Models (LLMs) into existing systems, workflows, products, and enterprise platforms using APIs, orchestration frameworks, and custom pipelines.
• Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality, accuracy, explainability, and contextual relevance.
• Engineer and optimize prompt orchestration, agentic workflows, and inference pipelines for production use.
• Develop prototypes and production-grade solutions leveraging open-source and commercial foundation models.
• Architect and implement robust RAG pipelines, including ingestion, indexing, retrieval, reranking, and response generation.
• Design and optimize data chunking strategies (semantic, recursive, token-based, metadata-aware chunking) to improve retrieval performance and model grounding.
• Create and manage embedding pipelines for structured and unstructured data sources.
• Implement and optimize vector search solutions using vector databases and similarity search technologies.
• Build and deploy GenAI solutions in cloud-native environments, with preference for AWS Bedrock, Amazon OpenSearch, and related AWS AI/ML services.
• Integrate LLM applications with enterprise APIs, microservices, databases, and existing application ecosystems.
• Support deployment of scalable and secure AI services using containers, serverless, and modern DevOps/MLOps practices.
• Optimize performance, latency, scalability, and observability of GenAI systems in production.
• Evaluate model performance, retrieval quality, hallucination reduction techniques, and system effectiveness.
• Implement guardrails, grounding strategies, and responsible AI controls for secure and trustworthy solutions.
• Stay current on emerging GenAI technologies, frameworks, and architectures, recommending innovations and improvements.
• Contribute to architecture decisions, technical roadmaps, and GenAI best practices across programs and teams.

Requirements

• Special Requirements: US Citizenship Required to obtain Public Trust Active DHS Clearance (preferred)
• Bachelor’s degree + 6 years of experience
• 3+ years of experience developing and optimizing solutions using Python or similar, with a strong focus on performance, scalability, and efficiency
• Extensive experience working with vector technology databases, designing and implementing solutions to efficiently store, search, and analyze high-dimensional data for real-time and large-scale applications
• GenAI and Bedrock experience

Preferred Qualifications

• Experience with AWS Bedrock, Amazon OpenSearch, and broader AWS AI/ML ecosystem
• Experience working with foundation models such as Claude, Llama, Mistral, OpenAI, or similar
• Familiarity with fine-tuning, model evaluation frameworks, and prompt engineering techniques
• Experience with MLOps/LLMOps, CI/CD pipelines, Docker, Kubernetes, and cloud deployment patterns
• Knowledge of security, governance, and responsible AI considerations for enterprise GenAI implementations
• Experience supporting federal, regulated, or enterprise-scale environments is a plus